Camera systems—and stereo camera systems in particular—react sensitively to dirt accumulation of any kind. When the camera system is a component of a monitoring system which automatically evaluates recorded images (e.g. a person counting system), there is a likelihood that detection errors consequently occur and remain unnoticed. In order to prevent impairments in the image quality and detection errors caused thereby, such camera systems can contain self-checking systems, which check whether there is any dirt accumulation or masking of the optical systems and therefore output respective warning signals. Most methods for optical self-diagnosis of a camera system which were developed up until now are based on gray-scale pictures supplied directly by the camera and require high computing power for evaluation and an enormous amount of memory.
Methods for the optical self-diagnosis of camera systems are already known from the state of the art. A rain sensor is described for example in the specification DE 10 2006 016 774 A1, in which rain is measured as a covering of the camera image on the basis of scattering of the pixel intensity.
As has already been mentioned above, such a solution comes with the disadvantage that high computing power and high memory capacity needs to be provided in order to evaluate the images.